Interpretive Summary: Peanut or groundnut is the mainstay to livelihood of millions of small-holder farmers residing in semi-arid tropic (SAT) regions of the world. The productivity in Asia (2217 kg/ha) and Africa (929 kg/ha) remained very poor as compared to Americas (3632 kg/ha). Low productivity due to exposure of crops to a range of abiotic (drought, heat) and biotic (foliar diseases, insect pests) stresses is the major cause. High level aflatoxin contamination is another major concern among the consumers. Thus, integration of genomics tools with conventional breeding approaches promises to handle the genetic bottlenecks and increase breeding efficiency leading to the more rapid development of improved cultivars. The peanut ‘mini core collection’ (184 accessions) representing diversity in the peanut ‘core collection’ and entire collection (>14, 000 accessions) was developed at the ICRISAT Genebank. The reference set is comprised of 300 genotypes from 48 countries representing SAT region and include all genotypes of the ‘mini core collection’. Multiple season phenotyping data was generated on the ‘reference set’ for many traits under several environments which include diseases resistance, oil/seed/nutritional quality, physiological/drought tolerance related traits, and yield/yield components. This study reports comprehensive analyses of the genome-wide association of this “reference set”, and identified a total of 524 highly significant associated markers for 36 traits. These markers will be validated and applied in breeding program.

Technical Abstract:
Peanut is an important and nutritious agricultural commodity and a livelihood of many small-holder farmers in the semi-arid tropics (SAT) of world which are facing serious production threats. Integration of genomics tools with on-going genetic improvement approaches is expected to facilitate accelerated development of improved cultivars. Therefore, high-resolution genotyping and multiple season phenotyping data for 50 important agronomic, disease and quality traits were generated on the ‘reference set’ of peanut. This study reports comprehensive analyses of allelic diversity, population structure, linkage disequilibrium (LD) decay and marker-trait association (MTA) in peanut. Distinctness of all the genotypes can be established by using either a single SSR or a combination of two SSR markers. As expected, DArT features (2.0 alleles/locus, 0.125 PIC) showed lower allele frequency and polymorphic information content (PIC) than SSRs (22.21 alleles /locus, 0.715 PIC). Both marker types clearly differentiated the genotypes of diploids from tetraploids. Multi-allelic SSRs identified three sub-groups (K = 3) while the LD simulation trend line based on squared-allele frequency correlations (r2) predicted LD decay of 15-20 cM in peanut genome. Detailed analysis identified a total of 524 highly significant MTAs (pvalue >2.1x10-6) with wide phenotypic variance (PV) range (5.81-90.09%) for 36 traits. These MTAs after validation may be deployed in improving biotic resistance, oil/ seed/ nutritional quality, drought tolerance related traits, and yield/ yield components.